Workshop Theme

Much progress has been made in recent years in creating probabilistic predictions of future climate from the data produced by multiple climate models. A growing number of statistical methods have been proposed and have been used to make probabilistic inferences of future and past climate e.g. model-weighting schemes, likelihood approaches, Bayesian hierarchical models, Reg-EM etc. However, there is no universal agreement on what constitutes a reliable and robust framework for inferring probabilistic predictions of real-world climate (or even if a sound framework exists?). This workshop will allow an open debate on these various modelling approaches and their respective strengths and weaknesses. In addition, the workshop aims to identify and formulate a few big and potentially solvable problems in the mathematics of probabilistic climate prediction that will form the basis for more detailed work by the Institute Fellows during the period of the programme.